Learning Dishonesty

Chiaki Sakama

Abstract

Children behave dishonestly as a way of managing problems in daily life.
Then our primary interest of this paper is how children learn dishonesty and
how one could model human acquisition of dishonesty using machine learning techniques.
We first observe the structural similarities between dishonest reasoning and induction,
and then characterize mental processes of dishonest reasoning using logic programming.
We argue how one develops behavioral rules for dishonest acts
and refines them to more advanced rules.